KR102395234B1 - A system for predicting drinking status and a prediction method using the same - Google Patents

Abstract

The present invention relates to a drinking status prediction system to promptly predict a subject's exercise ability for balance, reflexes, and the like and a drinking status prediction method using the same. According to the present invention, the drinking status prediction system comprises: a gait signal sensing unit including an acceleration sensor acquiring acceleration data of a subject, a gravity sensor acquiring the gravitational acceleration, a gyro sensor acquiring rotation data by measuring rotation speed, rotation degree, and tilt degree, a GPS sensor calculating real-time location data, a pressure sensor measuring air pressure to acquire altitude data, a proximity sensor determining whether there is the subject, and an image sensor acquiring image data of a face of the subject and a road surface; and a gait information analysis unit including a data storage unit storing gait analysis data, a display unit outputting the gait analysis data in a graphic user interface (GUI) form, a touch signal input unit performing a function of transmitting a command such as selecting or executing a predetermined graphic image displayed on the display unit, a wireless communication unit transmitting the gait analysis data, and a control unit generating and outputting the gait analysis data. In addition, the drinking status prediction method comprises: a gait signal sensing unit activation step of activating the gait signal sensing unit; a reference data acquisition step of securing initial reference points of acceleration data, gravity data, rotation data, position data, proximity data, altitude data, and image data; and a gait analysis step of processing the gait signal and analyzing exercise ability.

Description

A system for predicting drinking status and a prediction method using the same}

The present invention relates to a drinking state prediction system and predicting method, and more particularly, by measuring the motor ability for a person's sense of balance and reflexes, etc., through various sensors built in a mobile terminal and an application program driven based thereon. It is about the technology to determine whether it is possible to perform specific actions such as labor and labor.

Accidents caused by drinking include road traffic accidents and safety accidents at industrial sites.

Although there are differences according to individual physical conditions, alcohol consumption can cause major accidents by lowering the sense of balance, reflexes, and judgment. The conventional breathalyzer, which displays the level of drinking as a quantitative numerical value, is a relatively expensive device, and the burden of the initial introduction budget is inherent in this, and continuous sensor calibration is required for smooth operation. Due to the above-mentioned limitations, it is difficult to introduce and operate by expanding the base to general industrial sites, except for cases where government officials operate.

In a similar prior art, there is Republic of Korea Patent Publication No. 10-0652707 (2006.12.01.) 'a device and method for measuring breathability in a mobile communication terminal'. In the prior art, a memory for storing reference data for equilibrium state, movement, and direction according to the movement of a moving object by a certain distance in a steady state according to an experiment; an acceleration sensor for detecting acceleration by measuring a change in a magnetic field according to the movement of the user when the user moves a certain distance; a geomagnetic sensor for detecting geomagnetism according to the movement of the user when the user moves a certain distance; By processing the acceleration and geomagnetism as predetermined signals, the sensed data according to the movement and direction of movement of the user and the equilibrium state of the mobile communication terminal are compared with the reference data of the memory, and the drinking state is displayed on the display means based on the comparison result. It includes a control means for displaying, and when the sensed data is greater than the reference data, it is determined and displayed, and when the sensed data is less than the reference data, it is determined and displayed as a normal state.

In another prior art, there is a Korean Patent Application Laid-Open No. 10-2002-0091554 (2002.12.06.) 'a method for measuring breathability using a mobile communication terminal and a system therefor'. In the prior art, a mobile communication terminal connected to a mobile communication network and provided with a breathalyzer sensor for measuring the drinking data in the user's discharge respirator; Various information messages according to the drinking state are stored in advance, and the drinking data measured by the breathalyzer sensor provided in the mobile communication terminal is received through the mobile communication network to diagnose the drinking state corresponding to the drinking data, and diagnosis Reading a guide message corresponding to the result has been disclosed a technology including a breathalyzer server for transmitting to the mobile communication terminal through the mobile communication network.

In another prior art, there is Republic of Korea Patent Publication No. 10-2234164 (2021.03.25.) 'a system for preventing a drinking accident using a contact breath sensor and a method for preventing a drinking accident using the same'. In the prior art, a breathalyzer test result and identity authentication information are received from a user terminal equipped with a contact-type breathalyzer sensor to determine whether the user is drinking and whether the user is a registered user, and the user is a registered user and the drinking state is If not, a central control server that generates an authentication code and transmits it to the user terminal; A technology including a control terminal installed in a control target device and transmitting a control command to a device controller of the control target device when the authentication code transmitted to the user terminal is recognized has been disclosed.

However, in the above-mentioned prior arts, a technology for rapidly predicting the exercise ability of the subject's sense of balance and reflexes by outputting a virtual gait guide line and a touch request object on the display of the mobile terminal has not been proposed.

Republic of Korea Patent Publication No. 10-0652707 (2006.12.01.) ‘A device and method for measuring breathability in mobile communication terminals’ Republic of Korea Patent Publication No. 10-2002-0091554 (2002.12.06.) ‘Method for measuring breathability using mobile communication terminal and system therefor’ Republic of Korea Patent Publication No. 10-2234164 (2021.0 March 25.) ‘Drinking accident prevention system using contact breathability sensor and method of preventing drinking accident using the same’

An object of the present invention is to satisfy the technical needs required from the background of the above invention. Specifically, an object of the present invention is to solve the problems of the prior art and to overcome the proposed points, and a virtual walking guide line and a touch request object are output on the display of a mobile terminal, so that the target's sense of balance and reflection An object of the present invention is to provide a technology capable of rapidly predicting motor performance for nerves and the like. In addition, an object of the present invention is to provide a technology for predicting a person's drinking state in a specific environment where it is difficult to apply a conventional breathalyzer that displays the degree of drinking as a quantitative numerical value.

The technical problems to be achieved by the present invention are not limited to the above-mentioned problems, and other technical problems not mentioned can be clearly understood by those of ordinary skill in the art to which the present invention belongs from the description below. There will be.

The drinking state prediction system according to the present invention for achieving this object is an acceleration sensor that acquires the subject's acceleration data, a gravity sensor that acquires the gravitational acceleration, and a gyro that acquires rotation data by measuring the rotational speed, the degree of rotation, and the degree of inclination A walking signal that includes a sensor, a GPS sensor that calculates real-time location data, a pressure sensor that measures air pressure and acquires altitude data, a proximity sensor that determines the existence of the subject, and an image sensor that acquires image data of the subject's face and road surface A sensing unit; and a data storage unit for storing gait analysis data, a display unit for outputting gait analysis data in the form of a GUI, and a function of transmitting a command such as selecting or executing a specific graphic image displayed on the display unit and a gait information analysis unit including a touch signal input unit, a wireless communication unit for transmitting gait analysis data, and a controller for generating and outputting gait analysis data. In addition, the drinking state prediction method according to the present invention comprises the steps of activating the walking signal sensing unit in which the walking signal sensing unit is activated; a reference data acquisition step of securing initial reference points of acceleration data, gravity data, rotation data, position data, proximity data, altitude data, and image data; A gait analysis step of processing the gait signal and analyzing the exercise ability; characterized in that it is included.

As described above, in the present invention, a virtual walking guide line and a touch request object are output on the display of the mobile terminal, so that the exercise ability of the subject's sense of balance and reflexes can be quickly predicted. In addition, there is an effect that can perform the prediction of the person's drinking state in a specific environment where it is difficult to apply the conventional breathalyzer that displays the degree of drinking as a quantitative numerical value.

Various sensors, touch input type display modules, wireless communication modules, and processors, which are general components of conventional smart devices, are applied as a walking signal sensing unit, a display unit, a touch signal input unit, a wireless communication unit and a control unit for the configuration of a drinking state prediction system. By applying it, it is possible to provide an effect that can be used as a quick screening tool when measuring the target's sense of balance and motor ability for reflexes.

Provides clearer data by integrating the subject's physical movement element data measured from various sensors, facial recognition and road surface image data, and amplifying, removing noise, and A/D conversion of signal data before processing This is possible.

It is possible to calculate gait analysis data for evaluating the actual exercise ability of the person being evaluated, data required for user authentication and augmented reality implementation.

Validation may be performed through matching between the exercise ability reference data set by the evaluator and the exercise capacity measurement data of the evaluator, and the diagnosed or analyzed information may be stored and output.

By suggesting a method in which data measurement, data processing, and data analysis for gait signals are sequentially processed in time series through the drinking state prediction system, it is possible to provide an effect capable of analyzing the exercise ability of the subject.

By presenting the characteristic that the measurement of the walking signal is performed sequentially or simultaneously, it is possible to provide an effect suggesting that the control unit can perform both general sequential data processing and high-speed processing.

In the process of setting reference data for detecting change in multivariate data analysis, one camera (first image sensor = front camera) constituting the drinking state prediction system receives reference data for facial recognition of the subject. Another camera (second image sensor = rear camera) can provide the effect of collecting more detailed and binary reference data by classifying and collecting road image reference data for realization of augmented reality, respectively.

In connection with the road surface image data, the walking guideline can be implemented in the form of augmented reality, and at the same time, it can be linked with the exercise ability analysis to provide the effect of mutually sharing the exercise ability analysis results between the evaluator and the subject.

It is confirmed whether the subject recognizes the walking guideline, but by specifying the process of interaction between the walking guideline and the target mark, it is possible to provide the effect of whether the quantitative recognition of the assessee and the quantitative exercise ability evaluation of the assessor are further performed.

When analyzing exercise capacity, it is possible to provide the effect of performing quantitative evaluation that further includes information on the moving speed of the subject as well as evaluation by the gait guide line and target mark.

When detecting a gait error, a reference point that can generate any one or more of a warning message, a flashing alarm, and a warning sound can be presented.

It is possible to provide the effect that not only the exercise ability evaluation by the analysis of the degree of correspondence between the walking guide line and the target mark and the movement speed but also the exercise ability evaluation by the processing method of the unexpectedly output touch request object is made.

By proposing an example of adjusting the difficulty of the walking guideline, it is possible to provide an effect that can be implemented in various types of embodiments.

It is possible to provide the effect of implementing the exercise ability evaluation method in various types of embodiments by representing the footsteps of the subject in augmented reality in connection with the road surface image data and the gait guide line.

The technical effects of the present invention are not limited to the technical effects mentioned above, and other technical effects not mentioned can be clearly understood by those of ordinary skill in the art to which the present invention belongs from the description of the claims. There will be.

1 is an exemplary diagram 1 of a state in which a person to be evaluated is evaluated for a drinking state using the drinking state prediction system according to the present invention;
Figure 2 is an example of a state in which the person to be evaluated using the drinking state prediction system according to the present invention is evaluated 2;
Figure 3 is a configuration diagram showing the detailed configuration of the drinking state prediction system according to the present invention;
Figure 4 is a block diagram showing the detailed configuration of the walking information analysis unit according to the present invention;
5 is a flow chart showing a time-series flow of the drinking state prediction method using the drinking state prediction system according to the present invention;
6 is an exemplary diagram of a configuration of a walking guide line, a circular mark, a target mark, and speed information implemented in the display unit;
FIG. 7 is an example in which a walking guide line with increased difficulty is output on the display unit 1;
FIG. 8 is an example in which a walking guide line with increased difficulty is output on the display unit 2;
9 is an exemplary view in which a touch request object is generated on the display unit;
10 is an exemplary diagram in which a virtual footprint is output by linking a walking guide line and augmented reality to the display unit.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments in which the objects of the present invention can be specifically realized are described with reference to the accompanying drawings, which are for easier understanding of the present invention, and the scope of the present invention is not limited thereto. . In addition, in the description of the present embodiment, the same names and the same reference numerals are used for the same components, and an additional description thereof will be omitted.

The drinking state prediction system 10 of the present invention includes a gait signal sensing unit 100 and a gait information analysis unit 200 . If the drinking state prediction system 10 is in the form of a mobile terminal such as a personal digital assistant, a smart phone, a smart pad, a tablet PC, etc. equipped with an operating system in which a wired or wireless charging is possible battery module is built-in and driven and an application program can be driven All applications can be used, but it is not limited to the type of mobile terminal described above.

1 and 2 are exemplary views showing a state in which the subject A is evaluated for drinking using the drinking state prediction system 10 according to the present invention, and Figure 3 is a drinking state prediction system 10 according to the present invention. ) is a view showing the detailed configuration, and FIG. 4 is a diagram showing the detailed configuration of the walking information analysis unit 200 according to the present invention.

The configuration relationship between the gait signal sensing unit 100 and the gait information analysis unit 200 will be described in detail with reference to FIGS. 1 to 4 .

The walking signal sensing unit 100 includes an acceleration sensor 110 that acquires acceleration data by measuring the speed change applied to the subject A, the strength of the force, motion recognition, and the amount of movement speed change applied to the subject A, Gravity sensor 120 for calculating gravity data by measuring the acceleration of gravity, gyro sensor 130 for obtaining rotation data by measuring the rotational speed, rotational degree, and tilting degree applied to the subject A, the position and A GPS sensor 140 that receives time data and calculates real-time location data of the subject (A), a pressure sensor 150 that obtains altitude data by measuring the air pressure around the subject (A), and a drinking state prediction system (10) ), a proximity sensor 160 that determines whether the subject A is physically close to the It is composed of an image sensor 170 that

More specifically, the acceleration sensor 110 detects and measures the speed change in the x-axis, y-axis, and z-axis direction applied to the subject A, the strength of the force, motion recognition, and the amount of movement speed change applied to the subject A to obtain acceleration data. The calculation is used to calculate the walking speed and walking distance of the subject A through the acceleration data.

The gravity sensor 120 detects and measures the gravitational acceleration in the x-axis, y-axis, and z-axis directions applied to the subject (A) to calculate gravity data, and the drinking state prediction system 10 through the gravity data It is used to automatically change the reference position of the drinking state prediction system 10 by determining the horizontal position or vertical position of the.

The gyroscope sensor 130 detects and measures the rotational speed in the x-axis, y-axis, and z-axis directions applied to the subject A, the degree of rotation, and the angular speed for the degree of inclination to calculate the rotation data. It is used to calculate the gait angle of the subject (A) through the data.

The GPS sensor 140 receives the time information at which the drinking state prediction system 10 operates and the location information of the subject (A) from the GPS satellite to calculate real-time location data, to implement a quantitative location-based service. used

The pressure sensor 150 detects and measures the air pressure applied to the subject (A) and calculates altitude data. Through the altitude data, by inferring the topographic information where the subject (A) is located, quantitative momentum information and gait slope is used to calculate

The proximity sensor 160 determines whether there is a physical proximity between the subject A and the drinking state prediction system 10, and for predicting the drinking state, the acceleration sensor 110, the gravity sensor 120, and the gyroscope sensor ( 130), the GPS sensor 140, the pressure sensor 150, and the image sensor 170 are used to immediately activate and start the operation.

The image sensor 170 captures the face of the subject (A) when the subject (A) starts walking while holding the mobile terminal equipped with the drinking state prediction system (10) in his hand and at the same time as the subject (A) This is to take a picture of the road in the moving direction. To this end, the image sensor 170 acquires the face part image data of the subject A, and the first image sensor 171 for the purpose of real-time user authentication and the road in the direction in which the subject A moves A second image sensor 172 is further provided to acquire road surface image data for the city and to implement augmented reality (AR) through linkage with a walking guide line L, which will be described later.

4 is a view showing the detailed configuration of the gait information analyzing unit 200 according to the present invention. With reference to this, the configuration relationship of the gait information analyzing unit 200 will be described in detail as follows.

The gait information analysis unit 200 receives acceleration data, gravity data, rotation data, location data, proximity data, and altitude data from the gait signal sensing unit 100, and the gait speed, gait distance, and gait angle of the subject (A). , and performs a function of generating and outputting gait analysis data by performing gait state analysis including gait environment for gait position and gait slope.

To this end, the walking information analysis unit 200 includes a data storage unit 210 , a display unit 220 , a touch signal input unit 230 , a wireless communication unit 240 , and a control unit 250 , and the detailed technology described above The elements are described in detail as follows.

The data storage unit 210 includes a program area for storing a control program for controlling the operation of the gait information analysis unit 200, a temporary area for temporarily storing data generated during execution of the control program, It may include a data area for semi-permanently storing data and data necessary for executing the control program. The data area includes acceleration data, gravity data, rotation data, position data, proximity data, altitude data, image data of the subject's (A) face, road surface image data of the road in the direction in which the subject (A) moves, and analyzed walking speed. , walking distance, gait angle, gait position, and gait analysis data for gait slope can be stored.

The display unit 220 displays various data and information such as the operation state of the gait information analysis unit 200, gait analysis data, and location information of the subject A in text, icons, graphs, It performs a function of displaying any one or more of graphic images such as GUI (graphical user interface), still images, and moving pictures.

The touch signal input unit 230 performs a function in which the subject A transmits a command such as selecting or executing a specific graphic image displayed on the display unit 220 with a finger or a touch input tool. Allows you to enter a variety of information.

The wireless communication unit 240 is the acceleration data, gravity data, rotation data, position data, proximity data, altitude data, face part image data of the subject (A) collected by the walking signal sensing unit 100, the subject (A) moving A specific terminal for backing up or verifying raw data such as road surface image data of the road in the direction of travel and analysis data such as walking speed, walking distance, walking angle, walking position, and walking slope stored in the data storage unit 210 In order to transmit or transmit to (not shown in the drawing), a wireless communication function is performed in the same way as Wi-Fi, Bluetooth, Zigbee, and ultra-wideband.

The control unit 250 includes a data collection unit 251, a data analysis unit 252, and a data output unit 253, and the overall operation of the walking signal sensing unit 100 and the walking information analysis unit 200 according to the present invention. to control

The data collection unit 251 includes acceleration data, gravity data, rotation data, position data, proximity data, altitude data, face part image data of the subject (A), and the subject (A) moving from the walking signal sensing unit 100 An amplification module (not shown) for collecting road surface image data of the road in the direction of travel, amplifying the collected signal data, removing noise from the amplified signal data, and converting the noise-removed analog signal into a digital signal; At least one of a filter module (not shown) and an A/D conversion module (not shown) may be included.

The data analysis unit 252 includes an acceleration data analysis module 252a, a gravity data analysis module 252b, a rotation data analysis module 252c, a position data analysis module 252d, a proximity data analysis module 252e, and altitude data. The analysis module 252f and the image data analysis module 252g are further included, and the collected acceleration data, gravity data, rotation data, position data, proximity data, altitude data, the subject (A) face part image data, the From the road surface image data of the road in the direction in which the subject (A) moves, gait analysis data for the subject (A)'s walking speed, gait distance, gait angle, gait position, gait slope, user authentication information, and road surface information are generated and output do.

The data output unit 253 stores gait analysis data on the walking speed, walking distance, walking angle, walking position, and gait slope of the subject A analyzed by the data analysis unit 252 in the data storage unit 210 . It performs a function to be stored in or displayed through the display unit 220 .

5 is a flowchart showing a time-series flow of a method for predicting a drinking state using the drinking state prediction system 10 according to the present invention, and FIG. 6 is a walking guide line (L) implemented on the display unit 220, a circular mark (C), a target mark (T), is an exemplary view of the configuration of the speed information (V), Figures 7 and 8 are examples of the display unit 220 of the increased difficulty walking guide lines (L2, L3) are output 9 is an exemplary view in which a touch request object E is generated on the display unit 220, and FIG. 10 is a virtual footprint ( F) is an example of the output.

A method of predicting a drinking state will be described in detail with reference to FIGS. 5 to 10 as follows.

When the subject (A) grips the mobile terminal equipped with the drinking state prediction system 10 (S110), the proximity sensor 160 of the walking signal sensing unit 100 is activated (S120), the acceleration sensor 110, gravity The sensor 120, the gyroscope sensor 130, the GPS sensor 140, the pressure sensor 150, the operation of the sensors directly related to the acquisition of the gait information of the image sensor 170 is in either a sequential form or a simultaneous form A step of activating the walking signal sensing unit activated (S130) in one form (S100); is performed.

After the activating step (S100) of the walking signal sensing unit is performed, reference data acquisition step for acceleration data, gravity data, rotation data, position data, proximity data, altitude data, and image data in order to secure an initial reference point of data acquisition (S200); is performed. When the reference data acquisition step (S200) is performed, the first image sensor 171 constituting the image sensor 170 acquires the initial facial image data of the subject A, and the second image sensor 172 is the subject A ) acquires the initial road surface image data of the road to be moved.

After the reference data acquisition step (S200) is performed, the gait analysis step (S300); is performed. The gait analysis step (S300) will be described in detail as follows.

The road surface image data acquired by the second image sensor 172 is output on the display unit 220 in real time, and at the same time, the gait guide line L1 to be walked by the subject A is overlapped and displayed (S310) . The evaluation of the exercise ability is started by the subject (A) starting walking along the walking guide line (L1) (S320) .

When the subject A starts walking, the data collection unit 251 of the control unit 250 receives acceleration data, gravity data, rotation data, position data, proximity data, altitude data, and the subject from the walking signal sensing unit 100 . (A) Collecting facial image data and road image data of the road in the direction in which the subject (A) moves, amplifying the collected signal data, removing noise from the amplified signal data, and removing noise A walking signal processing step (S330) of converting to a digital signal is performed.

After the gait signal processing step (S330) is performed, data analysis is performed in the data analysis unit 252 of the control unit 250. The acceleration data analysis module 252a of the subject A holding the mobile terminal. Analyze the data, analyze the gravity data of the subject (A) holding the mobile terminal in the gravity data analysis module (252b), and the rotation data of the subject (A) holding the mobile terminal in the rotation data analysis module (252c) The location data analysis module 252d analyzes the location data of the subject A holding the mobile terminal, and the proximity data analysis module 252e continuously detects the proximity of the subject A holding the mobile terminal. Analyze proximity data on whether or not it is, and analyze the altitude data of the subject (A) holding the mobile terminal in the altitude data analysis module (252f), and image data of the face part for the subject (A) in the image data analysis module (252g) By analyzing the road surface image data of the road to be moved by and the subject (A), gait analysis data for the subject (A)'s walking speed, walking distance, gait angle, gait position, gait slope, user authentication information, and road surface information are generated. The exercise ability analysis step (S340) is performed.

The exercise ability analysis step (S340) will be described in detail as follows.

The subject (A) walks while maintaining a sense of balance along the gait guide line (L1) while walking so that the circular mark (C) is located in the center without contacting the target mark (T) Whether the sense of balance is maintained Perform exercise ability evaluation (S341) . In addition, the display unit 220 further displays the speed information (V) for the requested walking speed required for the subject A and the current speed at which the subject A is walking, and through this, the walking speed can be maintained constant. An exercise ability evaluation is made as to whether there is (S342) .

If the circular mark (C) touches or deviates from the target mark (T) in the process of the subject (A) walking, and the requested speed for exercise ability evaluation and the current speed at which the subject is walking do not match, the speed information (V) When one or more gait errors are detected among the cases in which an error occurs (S343) , a warning message is output to the display unit 220, a warning message is issued by flashing the display unit 220, or provided in a mobile terminal A warning sound is generated from the loudspeaker (S344) .

The above-described motor ability analysis step (S340) is to analyze the balance sense of the subject (A) and the motor ability for the reflexes. In order to further evaluate the motor ability for the reflexes, the reflex evaluation step (S345) is More may be included.

The reflex evaluation step (S346) may be performed at any time during the process of performing the exercise ability analysis step (S340), and as shown in FIG . E) is generated to measure the exercise ability for the reflex nerve of the subject (A). In the case of the touch request object E, when symbols such as numbers or English characters are randomly output, the subject A moves the touch request object E in ascending or descending order with the finger of the subject A or a touch input tool (Fig. The reflexes are evaluated by inputting a touch signal to the touch signal input unit 230 within a predetermined period of time, such as (not shown).

After the exercise ability analysis step (S340) is performed, acceleration data, gravity data, rotation data, position data, proximity data, altitude data, and the subject A in the data storage unit 210 of the walking information analysis unit 200 ) Motion information storage step ( S350) is performed,

If, in the exercise ability analysis step (S340), the subject (A) is considered to have lowered motor ability such as balance and reflexes due to drinking, the display unit 220 displays as shown in FIGS. 7 and 8 . As the gait guide lines L2 and L3 with increased gait difficulty are output, the gait analysis of the subject A can be further performed. It is not limited to the shape of the gait guide lines L1, L2, and L3, and the number of executions is not limited, and it is preferable that the gait evaluation be performed at least three times in order to secure the reliability of the exercise evaluation and to calculate the average value.

In addition, as shown in FIG. 10, by linking the walking guide line L and augmented reality so that the virtual footprint F is output to the display unit 220, the subject A measures the exercise ability for the sense of balance and reflexes, etc. In the process of doing so, it is preferable that it can be used to improve the understanding of the evaluation method based on the drinking state prediction system 10 or to improve the accuracy of the evaluation result.

Although the above has been described with reference to the drawings according to the embodiment of the present invention, it is possible for those of ordinary skill in the art to make various applications, modifications and adaptations within the scope of the present invention based on the above contents. will be. Accordingly, the true scope of protection of the present invention should be defined only by the appended claims.

A : Evaluated
10: Drinking state prediction system
100: walking signal sensing unit
110: acceleration sensor 120: gravity sensor
130: gyroscope sensor 140: GPS sensor
150: pressure sensor 160: proximity sensor
170: image sensor
171: first image sensor
172: second image sensor
200: gait information analysis unit
210: data storage unit 220: display unit
230: touch signal input unit 240: wireless communication unit
250: control unit
251: data collection unit
252: data analysis unit
252a: acceleration data analysis module
252b: Gravity data analysis module
252c: rotation data analysis module
252d : Location data analysis module
252e: Proximity data analysis module
252f: Advanced data analysis module
252g : Image data analysis module
253: data output unit

Claims (14)

In the drinking state prediction system,
Acceleration sensor 110 for acquiring acceleration data of the subject A, gravity sensor 120 for acquiring gravitational acceleration, gyro sensor 130 for acquiring rotation data by measuring rotational speed, rotational degree, and tilting degree, real-time A GPS sensor 140 for calculating location data, a pressure sensor 150 for acquiring altitude data by measuring air pressure, a proximity sensor 160 for determining whether the subject A exists, and the face and road surfaces of the subject A A walking signal sensing unit 100 including an image sensor 170 for acquiring image data; and
A data storage unit 210 for storing gait analysis data, a display unit 220 for outputting gait analysis data in a GUI form, and a command to select or execute a specific graphic image displayed on the display unit 220 are transmitted. and a gait information analysis unit 200 including a touch signal input unit 230 for performing a function, a wireless communication unit 240 for transmitting gait analysis data, and a controller 250 for generating and outputting gait analysis data; and ,
The display unit 220,
The drinking state prediction system, characterized in that the road surface image data obtained from the image sensor is output, and at the same time, the gait guide line to be walked by the person being evaluated is overlapped and output. The method of claim 1,
The control unit 250 includes acceleration data, gravity data, rotation data, location data, proximity data, altitude data, face part image data of the subject (A), and the road in which the subject (A) moves from the walking signal sensing unit 100 . A drinking state prediction system, characterized in that it includes a data collection unit 251 for collecting road surface image data of the. The method of claim 1,
The control unit 250 includes a data analysis unit 252 that generates and outputs gait analysis data for the subject A's walking speed, walking distance, gait angle, gait position, gait slope, user authentication information, and road surface information. Drinking state prediction system, characterized in that it becomes. The method of claim 1,
The control unit 250 stores the gait analysis data of the subject A in the data storage unit 210 or includes a data output unit 253 that performs a function of displaying it through the display unit 220. A drinking state prediction system characterized by. In the drinking state prediction method,
Activating step (S100) of the walking signal sensing unit in which the walking signal sensing unit 100 is activated;
Acceleration data, gravity data, rotation data, position data, proximity data, altitude data, reference data acquisition step (S200) of securing an initial reference point of the image data;
A gait analysis step (S300) of processing the gait signal and analyzing the exercise ability; is included,
The gait analysis step (S300) is,
The road surface image data acquired from the second image sensor 172 is output in real time, and at the same time, the walking guide line L1 is overlapped and displayed. A method for predicting drinking state, characterized in that the exercise ability analysis step (S340) in which gait analysis data is generated for gait angle, gait position, gait slope, user authentication information, and road surface information is further included. 6. The method of claim 5,
In the step of activating the walking signal sensing unit (S100), the proximity sensor 160 is activated, and the acceleration sensor 110, the gravity sensor 120, the gyroscope sensor 130, the GPS sensor 140, and the pressure sensor 150 are activated. , A drinking state prediction method, characterized in that the operation of the image sensor 170 is activated in either a sequential form or a simultaneous form. 6. The method of claim 5,
In the reference data acquisition step (S200), the first image sensor 171 acquires the initial facial image data of the subject A, and the second image sensor 172 acquires road surface image data State Prediction Method. delete 6. The method of claim 5,
The exercise ability analysis step (S340) is evaluated whether the circular mark (C) is located in the center without contacting the target mark (T) while the subject (A) walks while maintaining a sense of balance along the walking guide line (L1) A drinking state prediction method, characterized in that the balance evaluation step (S341) is further included. 6. The method of claim 5,
The exercise ability analysis step (S340) is a gait to evaluate whether the walking speed is maintained constant by further displaying the speed information (V) for the requested walking speed required for the subject (A) and the current speed at which the subject (A) is walking Drinking state prediction method, characterized in that the speed evaluation step (S342) is further included. 6. The method of claim 5,
The exercise ability analysis step (S340) is a gait error detection step of detecting a case in which the circular mark (C) touches or deviates from the target mark (T), and the requested speed and the current speed at which the subject A is walking does not match (S343) Drinking state prediction method, characterized in that it is further included. 6. The method of claim 5,
The exercise ability analysis step (S340) is a reflex evaluation step (S345) in which the subject (A) inputs a touch signal to the touch request object (E) within a predetermined time (S345). 6. The method of claim 5,
In the exercise ability analysis step (S340), if the subject (A) is considered to have reduced sense of balance and reflexes, the gait guide lines (L2, L3) with increased gait difficulty are output to further analyze the gait of the subject (A) Drinking state prediction method, characterized in that carried out. 14. The method according to any one of claims 5 to 7 and 9 to 13,
The walking guide lines (L1, L2, L3) are linked to augmented reality so that a virtual footprint (F) is output to the display unit (220), and a sense of balance and reflexes of the subject (A) are measured. State Prediction Method.

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